Omnichannel Is Dead. Long Live Omnichannel.

"Data-Driven Thinking" is written by members of the media community and contains fresh ideas on the digital revolution in media.

Today’s column is written by Mike Lempner, a customer intelligence practice executive at Infinitive.

Maybe it’s a sign of the maturation of digital marketing or just the reality setting in, but there is emerging buzz in the industry that the dream of true omnichannel customer awareness is dead. It’s a nonexistent pot of gold at the end of the rainbow, some say. A unicorn. A holy grail that will never be found.

Theoretically, such comprehensive views are still possible, given massive computing firepower and budgets, speaking of unicorns. Practically, this omnichannel vision is basically impossible, given the means and operations of most marketing organizations.

That said, the omnichannel dream shouldn’t simply die, but rather morph into a more feasible and dynamic vision of multidimensional customer intelligence. Such an approach would prioritize the most important customer information, but not necessarily all the possible customer information. Think about getting to “right-sized,” instead of “super-sized,” customer views.

Marketers should seek to leverage the precise data points and unique data combinations that can move the needle on influencing customer behavior within specific interactions and lead to more personalized offers across multichannel campaigns. Call the new vision “optichannel” customer knowledge.

Deepening customer intelligence and generating more useful insight are always worthy goals, even if the nirvana of total customer awareness at all times is out of reach. Rest assured that there is still plenty of bliss to be had by organizations that can focus on the most important channels and information.

Beyond Omnichannel

So how did we come to arrive to the post-omnichannel world? And what’s the right path ahead?

To a large extent, we’ve reached the limits of traditional analytical approaches leveraging data warehouses and other big-footprint data sources. The information housed therein was just too large and cumbersome to analyze meaningfully or at the pace the digital marketing world demands.

There were practical reasons, such as data quality issues, misspellings and duplicate phone numbers and emails, that prevented us from achieving true 360-degree views. And then there were strategic reasons – diminishing returns in trying to get dated transactional or all possible channel data, for example – that such views became somewhat irrelevant.

Big data platforms now enable us to store and analyze massive quantities of data in various formats, but the focus has been too much on getting all data and not the right and relevant data. Data lakes have turned into puddles and swamps, leaving the business without the significant value or insights despite heavy funding and effort. Determining the right and relevant data requires a balance of business knowledge, data science and analytical problem-solving skills.

So, over time, the focus has shifted to getting the most useful and actionable insights and putting them to work quickly. Indeed, speed, agility and focus are the characteristics businesses need when it comes to optimizing cross-channel marketing campaigns.

Today, marketers seeking better cross-channel performance must prioritize identity resolution, which involves the ability to link a device with a cookie and to an individual or household. This offers large potential benefit across not only digital channels, but in ensuring ads and offers reach the right people without duplicating impressions. Additionally, identity resolution should include the management of individuals and all of their contact points, including phone, email and address.

Better Technology

The technology is rapidly enabling such capabilities. Today, there are a range of tools and technologies that can quickly marry structured and unstructured data to identify the most important attributes for customer profitability. Data management platforms (DMPs) for instance, enable companies to target lookalike prospects who closely resemble top customers.

DMPs are also valuable in that they give marketers insight and confidence that psychographic and demographic data from third parties is actually useful and actionable. Again, we’ve learned that more attributes don’t necessarily move the needle on cross-channel marketing, but the right, actionable attributes certainly do.

It’s also important to remember that because the most critical attributes can change over time, even at different points along the conversion journey, marketers must be willing to test different attributes to see which provide the most lift and which are correlated with the optimal customer segments. This ability to avoid lock-in with third-party data vendors is another benefit of DMPs, which typically provide the flexibility to experiment with different data sets.

There is, of course, farther to go on the customer intelligence journey. It remains difficult to analyze some channels at scale, such as video, out-of-home and set-top box advertising. Mobile channels also present real challenges when it comes to identifying users and their interactions.

Organizational work must also be done regarding processes and governance. Large companies with diverse businesses may need to decide which product line or business unit gets first crack at making offers to website visitors. Marketing groups often exist in silos by product, so it is important to ensure offers are based upon the customer’s interest (e.g., contextual marketing) and not just based upon what the company wants to pitch or which department is next in line.

Data quality issues remain a big barrier, too. There should be clear standards and parameters for tracking how activities are matched and integrated across systems – say, CRM and transactional systems. Different data will be captured for different interactions (offering a coupon versus scheduling a service call), but the core data must be captured accurately and consistently to streamline user tracking across channels.

It’s fair to say that we’ve reached a certain stage in the development of data-driven marketing where many leading organizations realize that “good enough” is often preferable to “perfect” in the realm of customer intelligence. They recognize the value of seeking more dynamic and flexible approaches to cross-channel marketing, as they move past the old focus on capturing every piece of data they could.

To put it another way, 360-degee customer views may not be a practical reality given some of the strategic and tactical challenges. And they may not be worth the effort, energy or budget anyway, since solid 270-degree customer views may be rich and actionable enough to let marketers move quickly and decisively across channels in seeking to attract new prospects or increase loyalty and engagement with existing customers.